An evaluation on KNN-SVM algorithm for detection and prediction of DDoS attack
Recently, damage caused by DDoS attacks increases year by year. Along with the advancement of communication technology, this kind of attack also evolves and it has become more complicated and hard to detect using flash crowd agent, slow rate attack and also amplification attack that exploits a vulne...
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Online Access: | http://psasir.upm.edu.my/id/eprint/52677/1/An%20evaluation%20on%20KNN-SVM%20algorithm%20for%20detection%20and%20prediction%20of%20DDoS%20attack.pdf http://psasir.upm.edu.my/id/eprint/52677/ https://www.researchgate.net/publication/305315176_An_Evaluation_on_KNN-SVM_Algorithm_for_Detection_and_Prediction_of_DDoS_Attack |
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my.upm.eprints.526772021-09-04T23:03:05Z http://psasir.upm.edu.my/id/eprint/52677/ An evaluation on KNN-SVM algorithm for detection and prediction of DDoS attack Yusof, Ahmad Riza’ain Udzir, Nur Izura Selamat, Ali Recently, damage caused by DDoS attacks increases year by year. Along with the advancement of communication technology, this kind of attack also evolves and it has become more complicated and hard to detect using flash crowd agent, slow rate attack and also amplification attack that exploits a vulnerability in DNS server. Fast detection of the DDoS attack, quick response mechanisms and proper mitigation are a must for an organization. An investigation has been performed on DDoS attack and it analyzes the details of its phase using machine learning technique to classify the network status. In this paper, we propose a hybrid KNN-SVM method on classifying, detecting and predicting the DDoS attack. The simulation result showed that each phase of the attack scenario is partitioned well and we can detect precursors of DDoS attack as well as the attack itself. Springer Fujita, Hamido Ali, Moonis Selamat, Ali Sasaki, Jun Kurematsu, Masaki 2016 Book Section PeerReviewed text en http://psasir.upm.edu.my/id/eprint/52677/1/An%20evaluation%20on%20KNN-SVM%20algorithm%20for%20detection%20and%20prediction%20of%20DDoS%20attack.pdf Yusof, Ahmad Riza’ain and Udzir, Nur Izura and Selamat, Ali (2016) An evaluation on KNN-SVM algorithm for detection and prediction of DDoS attack. In: Trends in Applied Knowledge-Based Systems and Data Science. Lecture Notes in Computer Science . Springer, Switzerland, pp. 95-102. ISBN 9783319420066; EISBN: 9783319420073 https://www.researchgate.net/publication/305315176_An_Evaluation_on_KNN-SVM_Algorithm_for_Detection_and_Prediction_of_DDoS_Attack 10.1007/978-3-319-42007-3_9 |
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Recently, damage caused by DDoS attacks increases year by year. Along with the advancement of communication technology, this kind of attack also evolves and it has become more complicated and hard to detect using flash crowd agent, slow rate attack and also amplification attack that exploits a vulnerability in DNS server. Fast detection of the DDoS attack, quick response mechanisms and proper mitigation are a must for an organization. An investigation has been performed on DDoS attack and it analyzes the details of its phase using machine learning technique to classify the network status. In this paper, we propose a hybrid KNN-SVM method on classifying, detecting and predicting the DDoS attack. The simulation result showed that each phase of the attack scenario is partitioned well and we can detect precursors of DDoS attack as well as the attack itself. |
author2 |
Fujita, Hamido |
author_facet |
Fujita, Hamido Yusof, Ahmad Riza’ain Udzir, Nur Izura Selamat, Ali |
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Book Section |
author |
Yusof, Ahmad Riza’ain Udzir, Nur Izura Selamat, Ali |
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Yusof, Ahmad Riza’ain Udzir, Nur Izura Selamat, Ali An evaluation on KNN-SVM algorithm for detection and prediction of DDoS attack |
author_sort |
Yusof, Ahmad Riza’ain |
title |
An evaluation on KNN-SVM algorithm for detection and prediction of DDoS attack |
title_short |
An evaluation on KNN-SVM algorithm for detection and prediction of DDoS attack |
title_full |
An evaluation on KNN-SVM algorithm for detection and prediction of DDoS attack |
title_fullStr |
An evaluation on KNN-SVM algorithm for detection and prediction of DDoS attack |
title_full_unstemmed |
An evaluation on KNN-SVM algorithm for detection and prediction of DDoS attack |
title_sort |
evaluation on knn-svm algorithm for detection and prediction of ddos attack |
publisher |
Springer |
publishDate |
2016 |
url |
http://psasir.upm.edu.my/id/eprint/52677/1/An%20evaluation%20on%20KNN-SVM%20algorithm%20for%20detection%20and%20prediction%20of%20DDoS%20attack.pdf http://psasir.upm.edu.my/id/eprint/52677/ https://www.researchgate.net/publication/305315176_An_Evaluation_on_KNN-SVM_Algorithm_for_Detection_and_Prediction_of_DDoS_Attack |
_version_ |
1710677132717326336 |
score |
13.18916 |